Triple
T32644859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 6 Below: Miracle on the Mountain |
E834571
|
entity |
| Predicate | hasRealPersonSubject |
P102195
|
FINISHED |
| Object | Eric LeMarque |
E2167703
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Eric LeMarque | Statement: [6 Below: Miracle on the Mountain, hasRealPersonSubject, Eric LeMarque]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRealPersonSubject Context triple: [6 Below: Miracle on the Mountain, hasRealPersonSubject, Eric LeMarque]
-
A.
basedOnRealPersonFor
Indicates that one entity is created, modeled, or inspired using a specific real person as its basis.
-
B.
hasHumanSubject
Indicates that an entity serves as the human participant or subject involved in an action, event, or relation.
-
C.
realPerson
chosen
Indicates that the referenced entity corresponds to an actual human individual, as opposed to a fictional, anonymous, or non-human entity.
-
D.
hasSubjectPeople
Indicates that something (such as a work, document, or record) has people as its primary subject or focus.
-
E.
hasPersona
Indicates that an entity possesses or is associated with a particular persona, role, or character profile.
- F. None of above.
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f3492e773c81908afc10651e46cad3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a030425fa1c81908748583513552d2b |
completed | May 12, 2026, 10:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a38dde27c248190bcab513f78267892 |
completed | June 22, 2026, 7:01 a.m. |
| PD | Predicate disambiguation | batch_6a0303ced28081908588b8a14c23efe9 |
completed | May 12, 2026, 10:41 a.m. |
Created at: May 1, 2026, 1:07 a.m.